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dc.contributor.authorJanes A
dc.contributor.authorRusso B
dc.contributor.editorWolter K
dc.contributor.editorSchieferdecker I
dc.contributor.editorGallina B
dc.contributor.editorCukier M
dc.contributor.editorNatella R
dc.contributor.editorIvaki N
dc.contributor.editorLaranjeiro N
dc.date.accessioned2020-03-30T10:26:48Z
dc.date.available2020-03-30T10:26:48Z
dc.date.issued2019
dc.identifier.isbn978-1-7281-5139-7
dc.identifier.urihttp://dx.doi.org/10.1109/ISSREW.2019.00067
dc.identifier.urihttps://ieeexplore.ieee.org/document/8990249
dc.identifier.urihttps://bia.unibz.it/handle/10863/13487
dc.description.abstractThe transition from monolith to microservices poses several challenges, like how to redistribute the features of system over  different microservices. During the transition, developers may also redesign or rethink system services significantly, which can have a strong impact on various quality aspects of the resulting system. Thus, the new system may be more or less performing depending on the ability of the developers to design microservices and the capability of the microservice architecture to represent the system.  Overall, a transition to microservices may or may not end up with the same or a better performing system. One way to control the migration to microservices is to continuously monitor a system by continuously collecting performance data and feeding the resulting data analysis back in the transition process. In DevOps, such continuous feedback can be exploited to re-tune the development and deployment of system's builds.  In this paper, we present PPTAM+, a tool to continuously assess the degradation of a system during a transition to microservices. In an in-production system, the tool can continuously monitor each microservice and provide indications of lost performance and overall degradation. The system is designed to be integrated in a DevOps process. The tool automates the whole process from collecting data for building the reference operational profile to streamline performance data and automatically adapt and regress performance tests on each build based the analysis' feedback obtained from tests of the previous build.   en_US
dc.languageEnglish
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation30th International Symposium on Software Reliability Engineering (ISSRE 2019) ; Berlin : 28.10.2019 - 31.10.2019
dc.rights
dc.titleAutomatic performance monitoring and regression testing during the transition from monolith to microservicesen_US
dc.typeBook chapteren_US
dc.date.updated2020-03-27T03:00:25Z
dc.publication.title2019 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)
dc.language.isiEN-GB
dc.description.fulltextnoneen_US


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